Overview

Dataset statistics

Number of variables18
Number of observations12493
Missing cells626
Missing cells (%)0.3%
Duplicate rows151
Duplicate rows (%)1.2%
Total size in memory1.5 MiB
Average record size in memory130.0 B

Variable types

Numeric13
Categorical3
Boolean2

Alerts

Dataset has 151 (1.2%) duplicate rowsDuplicates
Administrative is highly overall correlated with Administrative_DurationHigh correlation
Administrative_Duration is highly overall correlated with AdministrativeHigh correlation
BounceRates is highly overall correlated with ExitRatesHigh correlation
ExitRates is highly overall correlated with BounceRates and 1 other fieldsHigh correlation
Informational is highly overall correlated with Informational_DurationHigh correlation
Informational_Duration is highly overall correlated with InformationalHigh correlation
ProductRelated is highly overall correlated with ExitRates and 1 other fieldsHigh correlation
ProductRelated_Duration is highly overall correlated with ProductRelatedHigh correlation
VisitorType is highly imbalanced (60.1%)Imbalance
PageValues has 626 (5.0%) missing valuesMissing
Administrative has 5851 (46.8%) zerosZeros
Administrative_Duration has 5993 (48.0%) zerosZeros
Informational has 9828 (78.7%) zerosZeros
Informational_Duration has 10055 (80.5%) zerosZeros
ProductRelated_Duration has 763 (6.1%) zerosZeros
BounceRates has 5568 (44.6%) zerosZeros
PageValues has 9237 (73.9%) zerosZeros
SpecialDay has 11226 (89.9%) zerosZeros

Reproduction

Analysis started2024-06-08 03:56:53.246843
Analysis finished2024-06-08 03:57:04.017418
Duration10.77 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

Administrative
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3097735
Minimum0
Maximum27
Zeros5851
Zeros (%)46.8%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:04.065405image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile9
Maximum27
Range27
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.3253648
Coefficient of variation (CV)1.4396931
Kurtosis4.9469442
Mean2.3097735
Median Absolute Deviation (MAD)1
Skewness1.9919156
Sum28856
Variance11.058051
MonotonicityNot monotonic
2024-06-08T11:57:04.136037image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 5851
46.8%
1 1378
 
11.0%
2 1124
 
9.0%
3 927
 
7.4%
4 778
 
6.2%
5 584
 
4.7%
6 434
 
3.5%
7 344
 
2.8%
8 287
 
2.3%
9 225
 
1.8%
Other values (17) 561
 
4.5%
ValueCountFrequency (%)
0 5851
46.8%
1 1378
 
11.0%
2 1124
 
9.0%
3 927
 
7.4%
4 778
 
6.2%
5 584
 
4.7%
6 434
 
3.5%
7 344
 
2.8%
8 287
 
2.3%
9 225
 
1.8%
ValueCountFrequency (%)
27 1
 
< 0.1%
26 1
 
< 0.1%
24 4
 
< 0.1%
23 6
 
< 0.1%
22 4
 
< 0.1%
21 2
 
< 0.1%
20 2
 
< 0.1%
19 6
 
< 0.1%
18 12
0.1%
17 16
0.1%

Administrative_Duration
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3335
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.349079
Minimum0
Maximum3398.75
Zeros5993
Zeros (%)48.0%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:04.206408image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7
Q392.5
95-th percentile344.7
Maximum3398.75
Range3398.75
Interquartile range (IQR)92.5

Descriptive statistics

Standard deviation175.92375
Coefficient of variation (CV)2.189493
Kurtosis50.956139
Mean80.349079
Median Absolute Deviation (MAD)7
Skewness5.632885
Sum1003801
Variance30949.164
MonotonicityNot monotonic
2024-06-08T11:57:04.358736image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5993
48.0%
4 56
 
0.4%
5 53
 
0.4%
7 45
 
0.4%
11 42
 
0.3%
6 41
 
0.3%
14 37
 
0.3%
15 36
 
0.3%
9 35
 
0.3%
10 32
 
0.3%
Other values (3325) 6123
49.0%
ValueCountFrequency (%)
0 5993
48.0%
1.333333333 1
 
< 0.1%
2 15
 
0.1%
3 26
 
0.2%
3.5 4
 
< 0.1%
4 56
 
0.4%
4.333333333 1
 
< 0.1%
4.5 2
 
< 0.1%
4.75 1
 
< 0.1%
5 53
 
0.4%
ValueCountFrequency (%)
3398.75 1
< 0.1%
2720.5 1
< 0.1%
2657.318056 1
< 0.1%
2629.253968 1
< 0.1%
2407.42381 1
< 0.1%
2156.166667 1
< 0.1%
2137.112745 1
< 0.1%
2086.75 1
< 0.1%
2047.234848 1
< 0.1%
1951.279141 1
< 0.1%

Informational
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.50260146
Minimum0
Maximum24
Zeros9828
Zeros (%)78.7%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:04.424201image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.267123
Coefficient of variation (CV)2.5211289
Kurtosis26.89237
Mean0.50260146
Median Absolute Deviation (MAD)0
Skewness4.0319265
Sum6279
Variance1.6056008
MonotonicityNot monotonic
2024-06-08T11:57:04.483742image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 9828
78.7%
1 1054
 
8.4%
2 743
 
5.9%
3 380
 
3.0%
4 225
 
1.8%
5 102
 
0.8%
6 78
 
0.6%
7 36
 
0.3%
9 15
 
0.1%
8 14
 
0.1%
Other values (7) 18
 
0.1%
ValueCountFrequency (%)
0 9828
78.7%
1 1054
 
8.4%
2 743
 
5.9%
3 380
 
3.0%
4 225
 
1.8%
5 102
 
0.8%
6 78
 
0.6%
7 36
 
0.3%
8 14
 
0.1%
9 15
 
0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
16 1
 
< 0.1%
14 2
 
< 0.1%
13 1
 
< 0.1%
12 5
 
< 0.1%
11 1
 
< 0.1%
10 7
 
0.1%
9 15
0.1%
8 14
 
0.1%
7 36
0.3%

Informational_Duration
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1258
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.338417
Minimum0
Maximum2549.375
Zeros10055
Zeros (%)80.5%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:04.551752image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile195
Maximum2549.375
Range2549.375
Interquartile range (IQR)0

Descriptive statistics

Standard deviation140.06582
Coefficient of variation (CV)4.0789831
Kurtosis76.863124
Mean34.338417
Median Absolute Deviation (MAD)0
Skewness7.5988141
Sum428989.84
Variance19618.435
MonotonicityNot monotonic
2024-06-08T11:57:04.627031image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10055
80.5%
9 33
 
0.3%
6 26
 
0.2%
7 26
 
0.2%
10 26
 
0.2%
16 24
 
0.2%
12 23
 
0.2%
13 23
 
0.2%
8 22
 
0.2%
11 21
 
0.2%
Other values (1248) 2214
 
17.7%
ValueCountFrequency (%)
0 10055
80.5%
1 3
 
< 0.1%
1.5 1
 
< 0.1%
2 11
 
0.1%
2.5 1
 
< 0.1%
3 16
 
0.1%
3.5 1
 
< 0.1%
4 17
 
0.1%
5 18
 
0.1%
5.5 3
 
< 0.1%
ValueCountFrequency (%)
2549.375 1
< 0.1%
2256.916667 1
< 0.1%
2252.033333 1
< 0.1%
2195.3 1
< 0.1%
2166.5 1
< 0.1%
2050.433333 1
< 0.1%
1949.166667 1
< 0.1%
1830.5 1
< 0.1%
1779.166667 1
< 0.1%
1778 1
< 0.1%

ProductRelated
Real number (ℝ)

HIGH CORRELATION 

Distinct311
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.701273
Minimum0
Maximum705
Zeros39
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:04.699813image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median18
Q338
95-th percentile109
Maximum705
Range705
Interquartile range (IQR)31

Descriptive statistics

Standard deviation44.351149
Coefficient of variation (CV)1.3990337
Kurtosis31.214201
Mean31.701273
Median Absolute Deviation (MAD)13
Skewness4.3373629
Sum396044
Variance1967.0244
MonotonicityNot monotonic
2024-06-08T11:57:04.773897image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 625
 
5.0%
2 476
 
3.8%
3 463
 
3.7%
4 408
 
3.3%
6 405
 
3.2%
7 395
 
3.2%
5 389
 
3.1%
8 382
 
3.1%
10 330
 
2.6%
9 317
 
2.5%
Other values (301) 8303
66.5%
ValueCountFrequency (%)
0 39
 
0.3%
1 625
5.0%
2 476
3.8%
3 463
3.7%
4 408
3.3%
5 389
3.1%
6 405
3.2%
7 395
3.2%
8 382
3.1%
9 317
2.5%
ValueCountFrequency (%)
705 1
< 0.1%
686 1
< 0.1%
584 1
< 0.1%
534 1
< 0.1%
518 1
< 0.1%
517 1
< 0.1%
501 1
< 0.1%
486 1
< 0.1%
470 1
< 0.1%
449 1
< 0.1%

ProductRelated_Duration
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9551
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1192.8265
Minimum0
Maximum63973.522
Zeros763
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:04.841564image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1184.33333
median598.77857
Q31464.2096
95-th percentile4298.9298
Maximum63973.522
Range63973.522
Interquartile range (IQR)1279.8763

Descriptive statistics

Standard deviation1907.0686
Coefficient of variation (CV)1.5987813
Kurtosis137.318
Mean1192.8265
Median Absolute Deviation (MAD)500.44524
Skewness7.2534629
Sum14901981
Variance3636910.8
MonotonicityNot monotonic
2024-06-08T11:57:04.913336image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 763
 
6.1%
17 21
 
0.2%
8 17
 
0.1%
11 17
 
0.1%
7 17
 
0.1%
15 16
 
0.1%
19 15
 
0.1%
22 15
 
0.1%
12 15
 
0.1%
13 14
 
0.1%
Other values (9541) 11583
92.7%
ValueCountFrequency (%)
0 763
6.1%
0.5 1
 
< 0.1%
1 2
 
< 0.1%
2.333333333 1
 
< 0.1%
2.666666667 1
 
< 0.1%
3 5
 
< 0.1%
4 10
 
0.1%
5 13
 
0.1%
5.333333333 1
 
< 0.1%
6 5
 
< 0.1%
ValueCountFrequency (%)
63973.52223 1
< 0.1%
43171.23338 1
< 0.1%
29970.46597 1
< 0.1%
27009.85943 1
< 0.1%
24844.1562 1
< 0.1%
23888.81 1
< 0.1%
23342.08205 1
< 0.1%
23050.10414 1
< 0.1%
21857.04648 1
< 0.1%
21672.24425 1
< 0.1%

BounceRates
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1872
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.022214841
Minimum0
Maximum0.2
Zeros5568
Zeros (%)44.6%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:04.982660image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.003174603
Q30.017123288
95-th percentile0.2
Maximum0.2
Range0.2
Interquartile range (IQR)0.017123288

Descriptive statistics

Standard deviation0.048426283
Coefficient of variation (CV)2.1799068
Kurtosis7.7489478
Mean0.022214841
Median Absolute Deviation (MAD)0.003174603
Skewness2.9508705
Sum277.53001
Variance0.0023451049
MonotonicityNot monotonic
2024-06-08T11:57:05.067027image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5568
44.6%
0.2 708
 
5.7%
0.066666667 135
 
1.1%
0.05 117
 
0.9%
0.028571429 115
 
0.9%
0.025 109
 
0.9%
0.04 102
 
0.8%
0.033333333 101
 
0.8%
0.016666667 99
 
0.8%
0.1 98
 
0.8%
Other values (1862) 5341
42.8%
ValueCountFrequency (%)
0 5568
44.6%
2.73 × 10-51
 
< 0.1%
3.35 × 10-51
 
< 0.1%
3.83 × 10-51
 
< 0.1%
3.94 × 10-51
 
< 0.1%
7.09 × 10-51
 
< 0.1%
7.27 × 10-51
 
< 0.1%
7.5 × 10-51
 
< 0.1%
8.01 × 10-51
 
< 0.1%
8.08 × 10-51
 
< 0.1%
ValueCountFrequency (%)
0.2 708
5.7%
0.183333333 1
 
< 0.1%
0.18 5
 
< 0.1%
0.176923077 1
 
< 0.1%
0.175 1
 
< 0.1%
0.166666667 4
 
< 0.1%
0.164285714 1
 
< 0.1%
0.164230769 1
 
< 0.1%
0.161904762 1
 
< 0.1%
0.16 3
 
< 0.1%

ExitRates
Real number (ℝ)

HIGH CORRELATION 

Distinct4777
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.043139975
Minimum0
Maximum0.2
Zeros76
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:05.140719image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.004574939
Q10.014285714
median0.025308642
Q30.05
95-th percentile0.2
Maximum0.2
Range0.2
Interquartile range (IQR)0.035714286

Descriptive statistics

Standard deviation0.048566624
Coefficient of variation (CV)1.1257917
Kurtosis4.0104596
Mean0.043139975
Median Absolute Deviation (MAD)0.014212075
Skewness2.1462458
Sum538.94771
Variance0.002358717
MonotonicityNot monotonic
2024-06-08T11:57:05.223392image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2 718
 
5.7%
0.1 346
 
2.8%
0.05 343
 
2.7%
0.033333333 291
 
2.3%
0.066666667 269
 
2.2%
0.025 229
 
1.8%
0.04 214
 
1.7%
0.016666667 181
 
1.4%
0.02 167
 
1.3%
0.022222222 154
 
1.2%
Other values (4767) 9581
76.7%
ValueCountFrequency (%)
0 76
0.6%
0.000175593 1
 
< 0.1%
0.000250438 1
 
< 0.1%
0.000262123 1
 
< 0.1%
0.000263158 1
 
< 0.1%
0.000292398 1
 
< 0.1%
0.000409836 1
 
< 0.1%
0.000446429 1
 
< 0.1%
0.000468384 1
 
< 0.1%
0.000480769 1
 
< 0.1%
ValueCountFrequency (%)
0.2 718
5.7%
0.192307692 1
 
< 0.1%
0.188888889 2
 
< 0.1%
0.186666667 4
 
< 0.1%
0.183333333 2
 
< 0.1%
0.181818182 1
 
< 0.1%
0.18034188 1
 
< 0.1%
0.18 3
 
< 0.1%
0.177777778 5
 
< 0.1%
0.175 6
 
< 0.1%

PageValues
Real number (ℝ)

MISSING  ZEROS 

Distinct2574
Distinct (%)21.7%
Missing626
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean5.8506274
Minimum0
Maximum361.76374
Zeros9237
Zeros (%)73.9%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:05.299096image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile38.045832
Maximum361.76374
Range361.76374
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.494055
Coefficient of variation (CV)3.161038
Kurtosis67.936624
Mean5.8506274
Median Absolute Deviation (MAD)0
Skewness6.4766172
Sum69429.395
Variance342.03008
MonotonicityNot monotonic
2024-06-08T11:57:05.368177image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9237
73.9%
53.988 6
 
< 0.1%
14.25648352 4
 
< 0.1%
1.023391581 4
 
< 0.1%
5.167133333 4
 
< 0.1%
8.497935484 4
 
< 0.1%
63.891 4
 
< 0.1%
9.869649371 3
 
< 0.1%
68.25041784 3
 
< 0.1%
5.408935339 3
 
< 0.1%
Other values (2564) 2595
 
20.8%
(Missing) 626
 
5.0%
ValueCountFrequency (%)
0 9237
73.9%
0.038034542 1
 
< 0.1%
0.067049546 1
 
< 0.1%
0.093546949 1
 
< 0.1%
0.098621403 1
 
< 0.1%
0.120699914 1
 
< 0.1%
0.129676893 1
 
< 0.1%
0.131837013 1
 
< 0.1%
0.139200623 1
 
< 0.1%
0.150650498 1
 
< 0.1%
ValueCountFrequency (%)
361.7637419 1
< 0.1%
360.9533839 1
< 0.1%
287.9537928 1
< 0.1%
270.7846931 1
< 0.1%
261.4912857 1
< 0.1%
258.5498732 1
< 0.1%
255.5691579 1
< 0.1%
254.6071579 1
< 0.1%
246.7585902 1
< 0.1%
239.98 1
< 0.1%

SpecialDay
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.061522453
Minimum0
Maximum1
Zeros11226
Zeros (%)89.9%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:05.427846image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.6
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.19909213
Coefficient of variation (CV)3.2360889
Kurtosis9.8570844
Mean0.061522453
Median Absolute Deviation (MAD)0
Skewness3.2958973
Sum768.6
Variance0.039637676
MonotonicityNot monotonic
2024-06-08T11:57:05.479623image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 11226
89.9%
0.6 357
 
2.9%
0.8 334
 
2.7%
0.4 244
 
2.0%
0.2 178
 
1.4%
1 154
 
1.2%
ValueCountFrequency (%)
0 11226
89.9%
0.2 178
 
1.4%
0.4 244
 
2.0%
0.6 357
 
2.9%
0.8 334
 
2.7%
1 154
 
1.2%
ValueCountFrequency (%)
1 154
 
1.2%
0.8 334
 
2.7%
0.6 357
 
2.9%
0.4 244
 
2.0%
0.2 178
 
1.4%
0 11226
89.9%

Month
Categorical

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size97.7 KiB
May
3248 
Nov
3021 
Mar
1934 
Dec
1756 
Oct
516 
Other values (8)
2018 

Length

Max length8
Median length3
Mean length3.0519491
Min length3

Characters and Unicode

Total characters38128
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFeb
2nd rowFeb
3rd rowFeb
4th rowFeb
5th rowFeb

Common Values

ValueCountFrequency (%)
May 3248
26.0%
Nov 3021
24.2%
Mar 1934
15.5%
Dec 1756
14.1%
Oct 516
 
4.1%
Sep 452
 
3.6%
Aug 444
 
3.6%
Jul 442
 
3.5%
June 292
 
2.3%
Feb 181
 
1.4%
Other values (3) 207
 
1.7%

Length

2024-06-08T11:57:05.541523image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
may 3248
26.0%
nov 3021
24.2%
mar 1934
15.5%
dec 1756
14.1%
oct 516
 
4.1%
sep 452
 
3.6%
aug 444
 
3.6%
jul 442
 
3.5%
june 292
 
2.3%
feb 181
 
1.4%
Other values (3) 207
 
1.7%

Most occurring characters

ValueCountFrequency (%)
a 5347
14.0%
M 5341
14.0%
y 3572
9.4%
o 3105
8.1%
N 3021
7.9%
v 3021
7.9%
e 2729
7.2%
c 2314
 
6.1%
r 1988
 
5.2%
D 1756
 
4.6%
Other values (13) 5934
15.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38128
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 5347
14.0%
M 5341
14.0%
y 3572
9.4%
o 3105
8.1%
N 3021
7.9%
v 3021
7.9%
e 2729
7.2%
c 2314
 
6.1%
r 1988
 
5.2%
D 1756
 
4.6%
Other values (13) 5934
15.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38128
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 5347
14.0%
M 5341
14.0%
y 3572
9.4%
o 3105
8.1%
N 3021
7.9%
v 3021
7.9%
e 2729
7.2%
c 2314
 
6.1%
r 1988
 
5.2%
D 1756
 
4.6%
Other values (13) 5934
15.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38128
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 5347
14.0%
M 5341
14.0%
y 3572
9.4%
o 3105
8.1%
N 3021
7.9%
v 3021
7.9%
e 2729
7.2%
c 2314
 
6.1%
r 1988
 
5.2%
D 1756
 
4.6%
Other values (13) 5934
15.6%

OperatingSystems
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1262307
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:05.591086image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile3
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.90970565
Coefficient of variation (CV)0.42784899
Kurtosis10.373218
Mean2.1262307
Median Absolute Deviation (MAD)0
Skewness2.0477546
Sum26563
Variance0.82756438
MonotonicityNot monotonic
2024-06-08T11:57:05.645084image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 6674
53.4%
3 2615
 
20.9%
1 2609
 
20.9%
4 484
 
3.9%
8 79
 
0.6%
6 19
 
0.2%
7 7
 
0.1%
5 6
 
< 0.1%
ValueCountFrequency (%)
1 2609
 
20.9%
2 6674
53.4%
3 2615
 
20.9%
4 484
 
3.9%
5 6
 
< 0.1%
6 19
 
0.2%
7 7
 
0.1%
8 79
 
0.6%
ValueCountFrequency (%)
8 79
 
0.6%
7 7
 
0.1%
6 19
 
0.2%
5 6
 
< 0.1%
4 484
 
3.9%
3 2615
 
20.9%
2 6674
53.4%
1 2609
 
20.9%

Browser
Real number (ℝ)

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3574802
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:05.709006image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile5
Maximum13
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7168127
Coefficient of variation (CV)0.72824056
Kurtosis12.747345
Mean2.3574802
Median Absolute Deviation (MAD)0
Skewness3.2437959
Sum29452
Variance2.9474458
MonotonicityNot monotonic
2024-06-08T11:57:05.762001image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2 8079
64.7%
1 2485
 
19.9%
4 744
 
6.0%
5 473
 
3.8%
6 177
 
1.4%
10 166
 
1.3%
8 136
 
1.1%
3 105
 
0.8%
13 61
 
0.5%
7 49
 
0.4%
Other values (3) 18
 
0.1%
ValueCountFrequency (%)
1 2485
 
19.9%
2 8079
64.7%
3 105
 
0.8%
4 744
 
6.0%
5 473
 
3.8%
6 177
 
1.4%
7 49
 
0.4%
8 136
 
1.1%
9 1
 
< 0.1%
10 166
 
1.3%
ValueCountFrequency (%)
13 61
 
0.5%
12 11
 
0.1%
11 6
 
< 0.1%
10 166
 
1.3%
9 1
 
< 0.1%
8 136
 
1.1%
7 49
 
0.4%
6 177
 
1.4%
5 473
3.8%
4 744
6.0%

Region
Real number (ℝ)

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1541663
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size97.7 KiB
2024-06-08T11:57:05.810234image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile8
Maximum9
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4027528
Coefficient of variation (CV)0.76177111
Kurtosis-0.16633187
Mean3.1541663
Median Absolute Deviation (MAD)2
Skewness0.97631637
Sum39405
Variance5.7732209
MonotonicityNot monotonic
2024-06-08T11:57:05.866264image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 4827
38.6%
3 2430
19.5%
4 1201
 
9.6%
2 1153
 
9.2%
6 830
 
6.6%
7 771
 
6.2%
9 513
 
4.1%
8 448
 
3.6%
5 320
 
2.6%
ValueCountFrequency (%)
1 4827
38.6%
2 1153
 
9.2%
3 2430
19.5%
4 1201
 
9.6%
5 320
 
2.6%
6 830
 
6.6%
7 771
 
6.2%
8 448
 
3.6%
9 513
 
4.1%
ValueCountFrequency (%)
9 513
 
4.1%
8 448
 
3.6%
7 771
 
6.2%
6 830
 
6.6%
5 320
 
2.6%
4 1201
 
9.6%
3 2430
19.5%
2 1153
 
9.2%
1 4827
38.6%

TrafficType
Categorical

Distinct37
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size97.7 KiB
2
3763 
1
2374 
3
1970 
4
1039 
13
706 
Other values (32)
2641 

Length

Max length8
Median length1
Mean length1.2799968
Min length1

Characters and Unicode

Total characters15991
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th rowfour

Common Values

ValueCountFrequency (%)
2 3763
30.1%
1 2374
19.0%
3 1970
15.8%
4 1039
 
8.3%
13 706
 
5.7%
6 430
 
3.4%
10 428
 
3.4%
8 331
 
2.6%
5 246
 
2.0%
11 235
 
1.9%
Other values (27) 971
 
7.8%

Length

2024-06-08T11:57:06.013294image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2 3763
30.1%
1 2374
19.0%
3 1970
15.8%
4 1039
 
8.3%
13 706
 
5.7%
6 430
 
3.4%
10 428
 
3.4%
8 331
 
2.6%
5 246
 
2.0%
11 235
 
1.9%
Other values (27) 971
 
7.8%

Most occurring characters

ValueCountFrequency (%)
1 4055
25.4%
2 3956
24.7%
3 2676
16.7%
4 1051
 
6.6%
0 620
 
3.9%
e 529
 
3.3%
t 453
 
2.8%
6 432
 
2.7%
o 379
 
2.4%
8 341
 
2.1%
Other values (16) 1499
 
9.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15991
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 4055
25.4%
2 3956
24.7%
3 2676
16.7%
4 1051
 
6.6%
0 620
 
3.9%
e 529
 
3.3%
t 453
 
2.8%
6 432
 
2.7%
o 379
 
2.4%
8 341
 
2.1%
Other values (16) 1499
 
9.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15991
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 4055
25.4%
2 3956
24.7%
3 2676
16.7%
4 1051
 
6.6%
0 620
 
3.9%
e 529
 
3.3%
t 453
 
2.8%
6 432
 
2.7%
o 379
 
2.4%
8 341
 
2.1%
Other values (16) 1499
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15991
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 4055
25.4%
2 3956
24.7%
3 2676
16.7%
4 1051
 
6.6%
0 620
 
3.9%
e 529
 
3.3%
t 453
 
2.8%
6 432
 
2.7%
o 379
 
2.4%
8 341
 
2.1%
Other values (16) 1499
 
9.4%

VisitorType
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size97.7 KiB
Returning_Visitor
10703 
New_Visitor
1705 
Other
 
85

Length

Max length17
Median length17
Mean length16.099496
Min length5

Characters and Unicode

Total characters201131
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReturning_Visitor
2nd rowReturning_Visitor
3rd rowReturning_Visitor
4th rowReturning_Visitor
5th rowReturning_Visitor

Common Values

ValueCountFrequency (%)
Returning_Visitor 10703
85.7%
New_Visitor 1705
 
13.6%
Other 85
 
0.7%

Length

2024-06-08T11:57:06.076617image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-06-08T11:57:06.130207image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
returning_visitor 10703
85.7%
new_visitor 1705
 
13.6%
other 85
 
0.7%

Most occurring characters

ValueCountFrequency (%)
i 35519
17.7%
t 23196
11.5%
r 23196
11.5%
n 21406
10.6%
e 12493
 
6.2%
_ 12408
 
6.2%
V 12408
 
6.2%
s 12408
 
6.2%
o 12408
 
6.2%
R 10703
 
5.3%
Other values (6) 24986
12.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 201131
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 35519
17.7%
t 23196
11.5%
r 23196
11.5%
n 21406
10.6%
e 12493
 
6.2%
_ 12408
 
6.2%
V 12408
 
6.2%
s 12408
 
6.2%
o 12408
 
6.2%
R 10703
 
5.3%
Other values (6) 24986
12.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 201131
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 35519
17.7%
t 23196
11.5%
r 23196
11.5%
n 21406
10.6%
e 12493
 
6.2%
_ 12408
 
6.2%
V 12408
 
6.2%
s 12408
 
6.2%
o 12408
 
6.2%
R 10703
 
5.3%
Other values (6) 24986
12.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 201131
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 35519
17.7%
t 23196
11.5%
r 23196
11.5%
n 21406
10.6%
e 12493
 
6.2%
_ 12408
 
6.2%
V 12408
 
6.2%
s 12408
 
6.2%
o 12408
 
6.2%
R 10703
 
5.3%
Other values (6) 24986
12.4%

Weekend
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
False
9575 
True
2918 
ValueCountFrequency (%)
False 9575
76.6%
True 2918
 
23.4%
2024-06-08T11:57:06.177215image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Revenue
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
False
10563 
True
1930 
ValueCountFrequency (%)
False 10563
84.6%
True 1930
 
15.4%
2024-06-08T11:57:06.220892image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Interactions

2024-06-08T11:57:03.031631image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.003740image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.694243image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.475877image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.171817image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.857720image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.671788image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.398590image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.155639image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.003345image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.757997image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.484879image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.321952image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:03.082222image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.055817image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.748235image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.530320image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.225360image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.910231image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.720796image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.451693image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.210807image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.054343image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.812666image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.540169image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.374726image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:03.136223image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.106528image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.806719image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.586165image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.280721image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.968869image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.775057image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.507822image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.278650image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.119452image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.866682image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.609682image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.429721image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:03.191916image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.153608image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.857759image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.632639image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.330925image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.022919image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.826078image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.567560image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.333725image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.175958image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.918366image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.669684image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.478608image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:03.251594image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.200272image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.911891image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.684157image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.379409image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.077433image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.881432image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.621117image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.469866image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.228962image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.971943image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.724843image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.533611image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:03.310022image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.258496image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.029834image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.739164image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.434433image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.133440image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.939414image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.683663image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.525867image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.289115image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.028624image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.781951image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.587296image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:03.365556image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.312182image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.084379image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.793701image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.487079image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.196115image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.995823image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.743634image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.586728image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.350108image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.085230image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.912184image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.646428image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:03.424567image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.370964image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.141927image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.850698image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.544536image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.326078image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.055840image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.804758image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.650647image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.411670image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.143408image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.971893image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.705942image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:03.485080image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.427975image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.198654image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.906473image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.600303image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.391363image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.118624image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.862773image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.712172image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.474358image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.204972image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.031858image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.765531image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:03.550080image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.481743image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.253628image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.961834image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.652408image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.444708image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.174036image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.919806image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.772030image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.530668image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.263520image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.093395image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.820649image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:03.605705image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.531749image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.308192image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.012483image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.700908image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.493989image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.232048image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.975058image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.827038image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.584368image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.313625image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.150459image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.874291image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:03.659707image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.588196image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.367022image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.068640image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.753063image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.570591image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.289038image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.037767image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.886793image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.644399image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.374174image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.207153image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.929300image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:03.714070image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:54.640197image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:55.418179image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.117642image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:56.801670image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:57.619106image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:58.343038image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.093301image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:56:59.942564image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:00.697948image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:01.428250image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.263248image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-06-08T11:57:02.977252image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Correlations

2024-06-08T11:57:06.266815image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
AdministrativeAdministrative_DurationBounceRatesBrowserExitRatesInformationalInformational_DurationMonthOperatingSystemsPageValuesProductRelatedProductRelated_DurationRegionRevenueSpecialDayTrafficTypeVisitorTypeWeekend
Administrative1.0000.941-0.155-0.013-0.4330.3690.3630.053-0.0060.3290.4590.4200.0110.131-0.1260.0800.0860.039
Administrative_Duration0.9411.000-0.164-0.023-0.4370.3590.3540.024-0.0080.3180.4290.4120.0210.064-0.1320.1940.0070.000
BounceRates-0.155-0.1641.000-0.0490.6030.004-0.0030.0550.052-0.123-0.053-0.081-0.0180.1680.1350.1100.1230.050
Browser-0.013-0.023-0.0491.000-0.017-0.019-0.0120.0600.3720.0260.0430.0450.0560.0380.0190.1910.4690.059
ExitRates-0.433-0.4370.603-0.0171.000-0.185-0.1990.0620.021-0.309-0.520-0.478-0.0040.2440.1500.1150.1850.065
Informational0.3690.3590.004-0.019-0.1851.0000.9510.0140.0010.2210.3660.366-0.0200.077-0.0560.3780.0280.012
Informational_Duration0.3630.354-0.003-0.012-0.1990.9511.0000.0060.0040.2250.3580.361-0.0120.066-0.0560.1480.0080.006
Month0.0530.0240.0550.0600.0620.0140.0061.000-0.0050.0770.1150.105-0.0270.1730.0230.1700.1360.057
OperatingSystems-0.006-0.0080.0520.3720.0210.0010.004-0.0051.000-0.0100.0220.0250.0270.0710.0240.1930.4650.119
PageValues0.3290.318-0.1230.026-0.3090.2210.2250.077-0.0101.0000.3420.3580.0030.411-0.0730.0470.1090.035
ProductRelated0.4590.429-0.0530.043-0.5200.3660.3580.1150.0220.3421.0000.883-0.0210.126-0.0180.2370.0780.000
ProductRelated_Duration0.4200.412-0.0810.045-0.4780.3660.3610.1050.0250.3580.8831.000-0.0110.071-0.0460.4070.0350.004
Region0.0110.021-0.0180.056-0.004-0.020-0.012-0.0270.0270.003-0.021-0.0111.0000.012-0.0170.0800.1800.021
Revenue0.1310.0640.1680.0380.2440.0770.0660.1730.0710.4110.1260.0710.0121.000-0.0870.1710.1020.025
SpecialDay-0.126-0.1320.1350.0190.150-0.056-0.0560.0230.024-0.073-0.018-0.046-0.017-0.0871.0000.1080.0640.258
TrafficType0.0800.1940.1100.1910.1150.3780.1480.1700.1930.0470.2370.4070.0800.1710.1081.0000.3830.151
VisitorType0.0860.0070.1230.4690.1850.0280.0080.1360.4650.1090.0780.0350.1800.1020.0640.3831.0000.053
Weekend0.0390.0000.0500.0590.0650.0120.0060.0570.1190.0350.0000.0040.0210.0250.2580.1510.0531.000

Missing values

2024-06-08T11:57:03.803625image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-06-08T11:57:03.942167image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

AdministrativeAdministrative_DurationInformationalInformational_DurationProductRelatedProductRelated_DurationBounceRatesExitRatesPageValuesSpecialDayMonthOperatingSystemsBrowserRegionTrafficTypeVisitorTypeWeekendRevenue
000.000.010.0000000.2000000.2000000.00.0Feb1111Returning_VisitorFalseFalse
100.000.0264.0000000.0000000.1000000.00.0Feb2212Returning_VisitorFalseFalse
200.000.010.0000000.2000000.2000000.00.0Feb4193Returning_VisitorFalseFalse
300.000.022.6666670.0500000.1400000.00.0Feb3224Returning_VisitorFalseFalse
400.000.010627.5000000.0200000.0500000.00.0Feb331fourReturning_VisitorTrueFalse
500.000.019154.2166670.0157890.0245610.00.0Feb2213Returning_VisitorFalseFalse
600.000.010.0000000.2000000.2000000.00.4Feb2433Returning_VisitorFalseFalse
710.000.000.0000000.2000000.2000000.00.0Feb121fiveReturning_VisitorTrueFalse
800.000.0237.0000000.0000000.1000000.00.8Feb2223Returning_VisitorFalseFalse
900.000.03738.0000000.0000000.0222220.00.4Feb2412Returning_VisitorFalseFalse
AdministrativeAdministrative_DurationInformationalInformational_DurationProductRelatedProductRelated_DurationBounceRatesExitRatesPageValuesSpecialDayMonthOperatingSystemsBrowserRegionTrafficTypeVisitorTypeWeekendRevenue
12483154.01237.016744.5000000.0133330.0337780.00.0Mar2262Returning_VisitorFalseFalse
12484154.01237.016744.5000000.0133330.0337780.00.0Mar2262Returning_VisitorFalseFalse
1248500.0157.05454.0000000.0000000.0500000.00.0Mar2236Returning_VisitorFalseFalse
1248600.0157.05454.0000000.0000000.0500000.00.0Mar2236Returning_VisitorFalseFalse
1248700.000.015432.5000000.0000000.0153850.00.0May2661Returning_VisitorFalseFalse
1248800.000.0564377.9833330.0042860.0222960.00.8May4114Returning_VisitorFalseFalse
1248900.000.0564377.9833330.0042860.0222960.00.8May4114Returning_VisitorFalseFalse
12490577.000.0943210.8482180.0021280.0209220.00.0Oct2232Returning_VisitorTrueFalse
12491577.000.0943210.8482180.0021280.0209220.00.0october2232Returning_VisitorTrueFalse
12492577.000.0943210.8482180.0021280.0209220.00.0Oct2232Returning_VisitorTrueFalse

Duplicate rows

Most frequently occurring

AdministrativeAdministrative_DurationInformationalInformational_DurationProductRelatedProductRelated_DurationBounceRatesExitRatesPageValuesSpecialDayMonthOperatingSystemsBrowserRegionTrafficTypeVisitorTypeWeekendRevenue# duplicates
2200.000.010.00.20.200.00.0Mar2211Returning_VisitorFalseFalse13
3000.000.010.00.20.200.00.0Mar3231Returning_VisitorFalseFalse6
1100.000.010.00.20.200.00.0Dec813920OtherFalseFalse5
3200.000.010.00.20.200.00.0May1113Returning_VisitorFalseFalse5
2800.000.010.00.20.200.00.0Mar3211Returning_VisitorFalseFalse4
3500.000.010.00.20.200.00.0May1143Returning_VisitorFalseFalse4
3800.000.010.00.20.200.00.0May2213Returning_VisitorFalseFalse4
5300.000.010.00.20.200.00.0Nov2211Returning_VisitorFalseFalse4
6800.000.027.00.00.10NaN0.0Nov2241Returning_VisitorFalseFalse4
7000.000.02162.00.00.050.00.0May2414Returning_VisitorFalseFalse4